Exploring druggable targets and inflammation-mediated pathways in cancer: a Mendelian randomization analysis integrating transcriptomic and proteomic data.

IF 4.8 3区 医学 Q2 CELL BIOLOGY
Hao Pan, Changqing Jing
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引用次数: 0

Abstract

Background: Cancer remains a predominant global health challenge, necessitating the ongoing exploration of novel biomarkers and therapeutic targets to improve diagnosis and treatment.

Methods: By integrating expression quantitative trait loci (eQTL) and protein quantitative trait loci (pQTL) data with genome-wide association studies (GWAS) data, we performed Mendelian randomization (MR) analysis to identify potential druggable targets at the gene expression and protein levels for multiple cancers. We conducted mediation analysis to explore whether inflammatory factors mediate the pathways linking identified druggable targets to cancer. Phenome-wide MR analysis, drug prediction, and molecular docking were employed to evaluate the medicinal potential.

Results: We finally identified five druggable targets: CDKN1A, FES, and PDIA3 were associated with breast cancer, whereas TP53 and VAMP8 were associated with prostate cancer. Mediation analysis identified six inflammatory proteins as potential mediators in the causal pathways from these druggable targets to cancer: caspase 8, interleukin-1-alpha, C-X-C motif chemokine 1, C-C motif chemokine 23, TNF-related apoptosis-inducing ligand, and interleukin-6. Subsequent analyses further provided evidence supporting the pharmaceutical potential of these five targets.

Conclusions: Our study identified five druggable targets causally associated with breast and prostate cancers, with six inflammatory proteins acting as potential mediators, providing novel insights into the treatment of these cancers.

探索癌症中可药物靶点和炎症介导的途径:整合转录组学和蛋白质组学数据的孟德尔随机化分析。
背景:癌症仍然是一个主要的全球健康挑战,需要不断探索新的生物标志物和治疗靶点来改善诊断和治疗。方法:通过整合表达数量性状位点(eQTL)和蛋白质数量性状位点(pQTL)数据与全基因组关联研究(GWAS)数据,进行孟德尔随机化(MR)分析,在基因表达和蛋白质水平上确定多种癌症的潜在药物靶点。我们进行了中介分析,以探讨炎症因子是否介导了将已确定的药物靶点与癌症联系起来的途径。采用全现象MR分析、药物预测、分子对接等方法评价药物潜力。结果:我们最终确定了5个可药物靶点:CDKN1A、FES和PDIA3与乳腺癌相关,而TP53和VAMP8与前列腺癌相关。中介分析确定了六种炎症蛋白作为从这些可药物靶点到癌症的因果通路中的潜在介质:caspase 8、白细胞介素-1- α、C-X-C基序趋化因子1、C-C基序趋化因子23、tnf相关的凋亡诱导配体和白细胞介素-6。随后的分析进一步提供了支持这五个靶点的药物潜力的证据。结论:我们的研究确定了5种与乳腺癌和前列腺癌有因果关系的可药物靶点,6种炎症蛋白作为潜在的介质,为这些癌症的治疗提供了新的见解。
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来源期刊
Inflammation Research
Inflammation Research 医学-免疫学
CiteScore
9.90
自引率
1.50%
发文量
134
审稿时长
3-8 weeks
期刊介绍: Inflammation Research (IR) publishes peer-reviewed papers on all aspects of inflammation and related fields including histopathology, immunological mechanisms, gene expression, mediators, experimental models, clinical investigations and the effect of drugs. Related fields are broadly defined and include for instance, allergy and asthma, shock, pain, joint damage, skin disease as well as clinical trials of relevant drugs.
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